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Data Analyst Data Science Jobs in Colorado (NOW HIRING)

Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics ... Engineering, or a related discipline. * Advanced proficiency in SQL with strong understanding of ...

Data Analyst

Boulder, CO · On-site

$70K - $80K/yr

Bachelor's degree in Computer Science, Information Technology, or a related field. * Experience: 3+ years of experience in data analysis, reporting, or BI-related roles. * Technical Skills:

Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics ... Engineering, or a related discipline. * Advanced proficiency in SQL with strong understanding of ...

Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics ... Engineering, or a related discipline. * Advanced proficiency in SQL with strong understanding of ...

Data Analyst

Lakewood, CO · On-site

$20.08/hr

The Data Analyst performs technical efforts including creating and modifying alarm accounts, buildings and contact information with various systems. Their primary purpose is the information ...

Data Analyst

Greenwood Village, CO · Hybrid

$50 - $60/hr

The Data Analyst will be instrumental in this process by transforming raw data from multiple sources into clear, actionable visualizations for stakeholders and executives. Key Responsibilities

The Data Analyst performs technical efforts including creating and modifying alarm accounts, buildings and contact information with various systems. Their primary purpose is the information ...

We are looking for a Mission Relevant Terrain - Cyber (MRT-C) Data Analyst in the Colorado Springs ... Bachelor's degree in Computer Science, Cyber Security, Information Systems, Data Science, or ...

Data Analyst

Englewood, CO · On-site

$63K - $90K/yr

Analyze data and provide actionable insights using SQL, Python, R, Tableau, and Microsoft/Google ... Bachelor's degree in a quantitative field (e.g., mathematics, statistics, computer science ...

MRT-C Data Analyst

Colorado Springs, CO · On-site

$70K - $95K/yr

We are looking for a Mission Relevant Terrain - Cyber (MRT-C) Data Analyst in the Colorado Springs ... Bachelor's degree in Computer Science, Cyber Security, Information Systems, Data Science, or ...

Analyze data and provide actionable insights using SQL, Python, R, Tableau, and Microsoft/Google ... Bachelor's degree in a quantitative field (e.g., mathematics, statistics, computer science ...

MRT-C Data Analyst

Colorado Springs, CO · On-site

$70K - $95K/yr

We are looking for a Mission Relevant Terrain - Cyber (MRT-C) Data Analyst in the Colorado Springs ... Bachelor's degree in Computer Science, Cyber Security, Information Systems, Data Science, or ...

Must demonstrate intermediate-advanced SQL Proficiency; experience using STATA or similar data science tool/language (Python or R) is helpful. Strong analytical competency with the ability to collect ...

Epic Clarity Data Analyst

Aurora, CO · On-site

$90K - $100K/yr

Must demonstrate intermediate-advanced SQL Proficiency; experience using STATA or similar data science tool/language (Python or R) is helpful. Strong analytical competency with the ability to collect ...

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Data Analyst Data Science information

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How much do data analyst data science jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for data analyst data science in Colorado is $36.69, according to ZipRecruiter salary data. Most workers in this role earn between $26.44 and $44.47 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Data analysts and data scientists can start their careers at any age, including 40 or older. Success in data science depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, which can be learned at any stage of life. Many professionals transition into data roles later in their careers with dedication and continuous learning.

How do Data Analysts in Data Science typically collaborate with other departments or teams?

Data Analysts in Data Science frequently work cross-functionally, partnering with teams such as engineering, product management, marketing, and business intelligence. They translate complex data findings into actionable insights and tailor their communication to both technical and non-technical stakeholders. Regular collaboration may involve participating in meetings to understand business needs, designing dashboards for different teams, and providing data-driven recommendations to support company objectives. This collaborative environment not only enhances project outcomes but also fosters continuous learning and professional growth.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data analysts often use this concept to focus on the most impactful variables or features during analysis and modeling to improve efficiency and accuracy.

What does a Data Analyst in Data Science do?

A Data Analyst in Data Science collects, processes, and analyzes large sets of data to help organizations make informed decisions. They use statistical techniques and data visualization tools to identify trends, patterns, and insights from data. Their responsibilities often include cleaning data, creating reports, and communicating findings to stakeholders. Data Analysts play a key role in helping businesses optimize operations, understand customer behavior, and solve complex problems using data-driven approaches.

Can data science work as a data analyst?

Data science and data analysis are related fields, but they have different focuses. Data scientists often develop models and algorithms using programming languages like Python or R, while data analysts primarily interpret data, generate reports, and use tools like Excel or SQL. Skills in statistical analysis, data visualization, and understanding business needs are essential for both roles, and some professionals transition between them based on experience and training.

What is the difference between Data Analyst Data Science vs Data Engineer?

AspectData Analyst Data ScienceData Engineer
Required SkillsStatistics, programming (Python, R), data visualizationDatabase systems, ETL pipelines, programming (Python, Java)
Work EnvironmentAnalyzing data, building models, reportingBuilding and maintaining data infrastructure
CertificationsData Science certifications, SQL, PythonCloud certifications, database management
Industry UsageBusiness analysis, predictive modelingData infrastructure, big data systems

Data Analyst Data Science focuses on analyzing data and creating models to inform decisions, while Data Engineers build the systems that collect, store, and process data. Both roles require programming skills and often overlap in tools like Python and SQL, but their core responsibilities differ significantly.

What are the key skills and qualifications needed to thrive as a Data Analyst in Data Science, and why are they important?

To thrive as a Data Analyst in Data Science, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Familiarity with tools like SQL, Python or R, and data visualization platforms such as Tableau or Power BI, along with industry-recognized certifications, is highly valued. Attention to detail, problem-solving abilities, and effective communication skills help you interpret data insights and convey findings to stakeholders. These skills are crucial for transforming raw data into actionable intelligence that drives strategic business decisions.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and communicating findings effectively. Data analysts who develop skills in machine learning, programming, and data visualization will continue to be valuable in the evolving data science environment.
What are popular job titles related to Data Analyst Data Science jobs in Colorado? For Data Analyst Data Science jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Data Analyst Data Science jobs? Cities in Colorado with the most Data Analyst Data Science job openings:
Infographic showing various Data Analyst Data Science job openings in Colorado as of June 2026, with employment types broken down into 1% As Needed, 74% Full Time, 19% Part Time, and 6% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $76,322 per year, or $36.7 per hour.

Full-time

Posted 15 days ago


Job description

Company Description

The Averna experience

Averna delivers industry-leading test solutions and services for communications and electronics device makers worldwide, accelerating product development, quality and innovation:

  • Be global@work: Serve international customers and collaborate with colleagues in Canada, Europe, the U.S., Mexico and Asia.
  • Drive innovation@work: Participate in the development of market-leading high-tech products in the Automotive & Transportation, Electric Vehicles, Consumer Electronics, Industrials and Life Sciences.  
  • Develop your talent@work: Contribute to thrilling projects that will stretch your skills and talent to the maximum.
  • Enjoy success@work: Be part of a fast-growing company with award-winning products and team.
  • Share your passion@work: Meet passionate people, enjoy our modern environment and dynamic atmosphere.
Job Description

Data Analyst - AI focused in Hardware Manufacturing, Quality & Reliability

Role Summary

This role sits at the intersection of data analytics, hardware manufacturing, quality & reliability engineering, and digital transformation. As an AIsavvy Data Analyst, you will generate valuedriven insights from fleetscale manufacturing, test, and deployment data while supporting New Product Introduction (NPI) and Product Operations teams.

You will transform complex manufacturing and quality concepts into datadriven metrics, intelligent dashboards, and AIenabled applications. You will also lead initiatives that modernize manual workflows into scalable, automated, and insightdriven systems-leveraging statistical analysis, cloud data platforms, and AI technologies.

Key Responsibilities

Data Analysis & Engineering

  • Extract, transform, and analyze fleetscale manufacturing, testing, deployment, and operational data using advanced SQL (DML).
  • Understand and translate manufacturing, quality, and reliability concepts into measurable, datadriven solutions and KPIs.
  • Perform statistical analysis on manufacturing test data to ensure data integrity, reliability, and readiness for automation and rootcause analysis.
  • Continuously provide feedback upstream to improve data quality, coverage, and performance.

AI, Automation & Intelligence

  • Identify and implement opportunities to automate manual workflows using AI and advanced analytics.
  • Develop AIdriven recommendation systems for data standards, anomaly detection, intelligent data mapping, and quality insights.
  • Support the integration of AI and ML services (e.g., Vertex AI, LLMs) into analytics workflows and intelligent applications.
  • Partner with engineers and product teams to embed AI capabilities into hardware NPI and manufacturing processes.

Visualization, Reporting & Executive Insights

  • Design, develop, and maintain interactive dashboards and reports using Looker Studio, Tableau, Power BI, or equivalent tools.
  • Visualize manufacturing performance, data quality scores, operational metrics, headcount status, and organizational spending.
  • Prepare executivelevel summaries and presentations that distill complex technical data into clear, actionable insights.
  • Provide leadership with realtime, decisionready visibility into manufacturing and operational health.

CrossFunctional Collaboration & Program Support

  • Interact professionally with engineers, product owners, suppliers, and subjectmatter experts across manufacturing, quality, IT, and operations.
  • Provide technical guidance to suppliers and engineering teams on optimal data collection, standards, and data warehousing solutions.
  • Support multiple parallel initiatives by tracking progress, identifying risks, and escalating delivery impediments when needed.
  • Facilitate change management through documentation, communication plans, and process training.
Qualifications

The ideal candidate in a few words:

Required Qualifications

  • Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics, Engineering, or a related discipline.
  • Advanced proficiency in SQL with strong understanding of data modeling and normalization best practices.
  • Proficiency in Python (or R) for data analysis, including experience with the PyData stack (NumPy, Pandas, Matplotlib, scikitlearn).
  • Strong analytical, problemsolving, and statistical analysis skills.
  • Proven experience creating dashboards, reports, and structured datasets to support business and engineering decisions.
  • Excellent verbal and written communication skills in English.

Preferred / NicetoHave Qualifications

  • 5+ years of experience working with cloud data warehouses such as Google BigQuery or equivalent platforms.
  • Familiarity with Google Cloud data products (Vertex AI, Colab, Cloud APIs).
  • 5+ years of experience building interactive dashboards in Looker Studio, Tableau, Power BI, or similar tools.
  • Practical experience with AI/ML models, Large Language Models (LLMs), and AIenabled workflow automation.
  • Domain experience in electronics manufacturing processes, quality engineering, test engineering, or reliability engineering.
  • Exposure to data governance, data quality management, or master data management concepts.
  • Familiarity with operational topics such as headcount planning, resource allocation, or vendor/contractor (TVC) tracking.
  • Fluency in Mandarin or French is a plus.
Additional Information

What's in It for You

  • Learn and grow through multiple cutting-edge projects 
  • Flexible work hours and remote work model #LI-REMOTE
  • Competitive benefits package and competitive total compensation
  • An additional day off for your birthday
  • Flex days paid between Christmas and New year's 
  • Be part of a company that puts ESG at the heart of its mission, for people, planet, and performance. 

Averna is committed to employment equity and to encouraging diversity and inclusion. We are pleased to consider all qualified applicants for employment, regardless of race, color, religion, sexual orientation, gender, national origin, age, disability, veteran status, or any other legally protected status.Â